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Title:Analiza učinkov ukrepa Politike razvoja podeželja za pomoč mladim prevzemnikom kmetijskih gospodarstev
Authors:ID Pavić, Lazar (Author)
ID Prišenk, Jernej (Mentor) More about this mentor... New window
ID Turk, Jernej (Comentor)
Files:.pdf DOK_Pavic_Lazar_2019.pdf (1,37 MB)
MD5: 1EA237442BECAA9788D170F3676CBD98
PID: 20.500.12556/dkum/eef873d7-5cf3-4d1c-9501-e9163f0a6a6e
 
Language:Slovenian
Work type:Doctoral dissertation
Typology:2.08 - Doctoral Dissertation
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:Namen doktorske disertacije z naslovom Analiza učinkov ukrepa Politike razvoja podeželja za pomoč mladim prevzemnikom kmetijskih gospodarstev je ugotavljanje rezultatov oziroma učinkov, ki jih je ukrep 112 (Pomoč mladim prevzemnikom kmetij) imel na izbrane agrarnoekonomske dejavnike kmetijskih gospodarstev na območju Slovenije. S tem namenom smo v prvem koraku razvili večje število modelov s pomočjo multiple regresije, ki smo jih v naslednjem koraku nadgradili z vključevanjem več skupin umetnih spremenljivk, ki opisujejo lastnosti kmetijskih gospodarstev in mladih prevzemnikov. Cilj doktorske disertacije je bil na podlagi razpoložljivih podatkov ugotoviti, v kolikšnem obsegu je sodelovanju v ukrepu 112 izboljšalo agrarnoekonomske dejavnike kmetijskih gospodarstev, in na podlagi tega podati smernice pri načrtovanju Skupne kmetijske politike (SKP) po letu 2020 za področje mladih prevzemnikov kmetijskih gospodarstev na območju Slovenije. Raziskava, ki je bila izvedena v okviru doktorske disertacije, je bila zasnovana na vzročno-posledičnih odnosih med dvema skupinama spremenljivk: odvisnimi in neodvisnimi. Za dodatno ugotavljanje uspešnosti izvedbe ukrepa 112 smo uporabili analizo skupin oziroma na podlagi rezultatov, ki jih ukrep imel na spremembo izbranih agrarnoekonomskih dejavnikov, poskušali vse kmetije razvrstiti v tri skupine glede na uspešnost izvedbe omenjenega ukrepa. Za razvrščanje v skupine smo uporabili nove spremenljivke, ki smo jih ustvarili z metodo glavnih komponent. Rezultati, ki smo jih predstavili v okviru doktorske disertacije, imajo tudi v širšem kontekstu pozitivne neposredne in posredne učinke na izzive, opredeljene v literaturi. Z njimi se bo Skupna kmetijska politika srečala po letu 2020, predvsem pa bodo prispevali k rasti delovnih mest, ki so podprta z inovacijami in prehodom na nove modele proizvodnje.
Keywords:razvoj podeželja, kmetijska politika, mladi prevzemniki, regresijski modeli, analiza skupin
Place of publishing:Maribor
Year of publishing:2019
PID:20.500.12556/DKUM-73992 New window
NUK URN:URN:SI:UM:DK:T4HARCTM
Publication date in DKUM:19.11.2019
Views:2831
Downloads:263
Metadata:XML DC-XML DC-RDF
Categories:FKBV
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:14.07.2019

Secondary language

Language:English
Title:Effect Analysis of a Rural Development Programme for Supporting Young Farmers in Taking Over Agricultural Holdings
Abstract:The purpose of the doctoral dissertation entitled "Effect Analysis of a Rural Development Programme for Supporting Young Farmers in Taking Over Agricultural Holdings" was to determine the results and effects of the measure 112 on the selected agroeconomic factors of Slovenian agricultural holdings. For this purpose, numerous multiple regression models were developed, which were then upgraded by involving several groups of dummy variables that describe the characteristics of agricultural holdings and young transferees. The main aim of the dissertation was to determine the extent to which the participation in the CAP 112 measure has improved the agroeconomic factors of the agricultural holdings and derive concrete guidance from this in the planning of CAP after 2020 from the field of young farmers in Slovenia. The research was based on causal-consequential relations between two groups of variables: dependent and independent variables. In order to further establish the success of the implementation of the CAP 112 measure, cluster analysis was used. Based on the results the CAP 112 measure had on the change of the selected agrarian economic factors, all agricultural holdings were classified into three groups. For the classification of farms into groups, new variables were created using the Principal Component Analysis. The results presented in this dissertation have positive direct and indirect effects on the challenges presented in the literature, that the Common Agricultural Policy will meet after 2020, in particular on contributing to the increase in jobs that are supported by innovation and switching to new production models.
Keywords:Rural Development, Agricultural Policy, Young Farmers, Regression Models, Cluster Analysis


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